{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,20]],"date-time":"2026-10-20T16:50:13Z","timestamp":1792515013208,"version":"4.5.0"},"reference-count":65,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T00:00:00Z","timestamp":1702425600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Medicina"],"abstract":"<jats:p>Background and Objectives: Frontotemporal dementia (FTD) is the second most common form of presenile dementia; however, its diagnosis has been poorly investigated. Previous attempts to diagnose FTD using quantitative electroencephalography (qEEG) have yielded inconsistent results in both spectral and functional connectivity analyses. This study aimed to introduce an accurate qEEG marker that could be used to diagnose FTD and other neurological abnormalities. Materials and Methods: We used open-access electroencephalography data from OpenNeuro to investigate the power ratio between the frontal and temporal lobes in the resting state of 23 patients with FTD and 29 healthy controls. Spectral data were extracted using a fast Fourier transform in the delta (0.5 \u2264 4 Hz), theta (4 \u2264 8 Hz), alpha (8\u201313 Hz), beta (&gt;13\u201330 Hz), and gamma (&gt;30\u201345 Hz) bands. Results: We found that the spectral power ratio between the frontal and temporal lobes is a promising qEEG marker of FTD. Frontal (F)-theta\/temporal (T)-alpha, F-alpha\/T-theta, F-theta\/F-alpha, and T-beta\/T-gamma showed a consistently high discrimination score for the diagnosis of FTD for different parameters and referencing methods. Conclusions: The study findings can serve as reference for future research focused on diagnosing FTD and other neurological anomalies.<\/jats:p>","DOI":"10.3390\/medicina59122155","type":"journal-article","created":{"date-parts":[[2023,12,13]],"date-time":"2023-12-13T04:14:42Z","timestamp":1702440882000},"page":"2155","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Quantitative Electroencephalography Markers for an Accurate Diagnosis of Frontotemporal Dementia: A Spectral Power Ratio Approach"],"prefix":"10.3390","volume":"59","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-6411-9761","authenticated-orcid":false,"given":"Jinwon","family":"Chang","sequence":"first","affiliation":[{"name":"Korean Minjok Leadership Academy, Hoengseong 25268, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chul","family":"Chang","sequence":"additional","affiliation":[{"name":"College of Medicine, Catholic University of Korea, Seoul 06591, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S96","DOI":"10.1017\/cjn.2016.25","article-title":"The prevalence and incidence of frontotemporal dementia: A systematic review","volume":"43","author":"Hogan","year":"2016","journal-title":"Can. J. Neurol. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1101\/cshperspect.a006239","article-title":"Epidemiology of Alzheimer disease","volume":"2","author":"Mayeux","year":"2012","journal-title":"Cold Spring Harb. Perspect. Med."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"126","DOI":"10.4088\/JCP.10m06382oli","article-title":"The diagnostic challenge of psychiatric symptoms in neurodegenerative disease: Rates of and risk factors for prior psychiatric diagnosis in patients with early neurodegenerative disease","volume":"72","author":"Woolley","year":"2011","journal-title":"J. Clin. Psychiatry"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"6581490","DOI":"10.1155\/2018\/6581490","article-title":"Usefulness of EEG techniques in distinguishing frontotemporal dementia from Alzheimer\u2019s disease and other dementias","volume":"2018","author":"Nardone","year":"2018","journal-title":"Dis. Markers"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1159\/000067973","article-title":"Quantitative EEG abnormalities and cognitive dysfunctions in frontotemporal dementia and Alzheimer\u2019s disease","volume":"15","author":"Lindau","year":"2003","journal-title":"Dement. Geriatr. Cogn. Disord."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1718","DOI":"10.1016\/j.clinph.2011.02.011","article-title":"Differences in quantitative EEG between frontotemporal dementia and Alzheimer\u2019s disease as revealed by LORETA","volume":"122","author":"Nishida","year":"2011","journal-title":"Clin. Neurophysiol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1177\/155005949602700204","article-title":"Quantitative EEG in frontotemporal dementia","volume":"27","author":"Yener","year":"1996","journal-title":"Clin. Electroencephalogr."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/0013-4694(81)90230-3","article-title":"Regional EEG analysis and regional cerebral blood flow in Alzheimer\u2019s and Pick\u2019s diseases","volume":"51","author":"Stigsby","year":"1981","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2343","DOI":"10.1016\/j.neurobiolaging.2011.12.011","article-title":"Quantitative EEG and LORETA: Valuable tools in discerning FTD from AD","volume":"33","author":"Caso","year":"2012","journal-title":"Neurobiol. Aging"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"521","DOI":"10.3389\/fnhum.2018.00521","article-title":"EEG frequency bands in psychiatric disorders: A review of resting state studies","volume":"12","author":"Newson","year":"2018","journal-title":"Front. Hum. Neurosci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1732","DOI":"10.1016\/j.clinph.2008.02.024","article-title":"Investigation of resting-state EEG functional connectivity in frontotemporal lobar degeneration","volume":"119","author":"Pijnenburg","year":"2008","journal-title":"Clin. Neurophysiol."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"de Haan, W., Pijnenburg, Y.A., Strijers, R.L., van der Made, Y., van der Flier, W.M., Scheltens, P., and Stam, C.J. (2009). Functional neural network analysis in frontotemporal dementia and Alzheimer\u2019s disease using EEG and graph theory. BMC Neurosci., 10.","DOI":"10.1186\/1471-2202-10-101"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.neurobiolaging.2016.03.018","article-title":"Different functional connectivity and network topology in behavioral variant of frontotemporal dementia and Alzheimer\u2019s disease: An EEG study","volume":"42","author":"Yu","year":"2006","journal-title":"Neurobiol. Aging"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3822","DOI":"10.1038\/s41598-017-04204-8","article-title":"Towards affordable biomarkers of frontotemporal dementia: A classification study via network\u2019s information sharing","volume":"7","author":"Dottori","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_15","first-page":"175","article-title":"A tutorial review of functional connectivity analysis methods and their interpretational pitfalls","volume":"9","author":"Bastos","year":"2015","journal-title":"Front. Syst. Neurosci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1007\/s10548-020-00757-6","article-title":"EEG Functional Connectivity is a Weak Predictor of Causal Brain Interactions","volume":"33","author":"Vink","year":"2020","journal-title":"Brain Topogr."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1002\/gps.1388","article-title":"The heterogeneity of frontotemporal dementia with regard to initial symptoms, qEEG and neuropathology","volume":"20","author":"Passant","year":"2005","journal-title":"Int. J. Geriatric. Psych."},{"key":"ref_18","first-page":"142","article-title":"Clinical diagnosis of frontal lobe dementia and Alzheimer\u2019s disease: Relation to cerebral perfusion, brain atrophy and electroencephalography","volume":"6","author":"Julin","year":"1995","journal-title":"Dementia"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1111\/j.1600-0404.1979.tb02933.x","article-title":"EEG and cognitive impairment in presenile dementia","volume":"59","author":"Johannesson","year":"1979","journal-title":"Acta Neurol. Scand."},{"key":"ref_20","first-page":"43","article-title":"Multichannel EEG frequency analysis and somatosensory-evoked potentials in patients with different types of organic dementia","volume":"4","author":"Gustafson","year":"1993","journal-title":"Dementia"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.ncl.2017.01.008","article-title":"Frontotemporal Dementia","volume":"35","author":"Olney","year":"2017","journal-title":"Neurol. Clin."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Thammasan, N., and Miyakoshi, M. (2020). Cross-frequency power-power coupling analysis: A useful cross-frequency measure to classify ICA-decomposed EEG. Sensors, 20.","DOI":"10.3390\/s20247040"},{"key":"ref_23","first-page":"175","article-title":"Electroencephalogram (EEG) stress analysis on alpha\/beta ratio and theta\/beta ratio","volume":"17","author":"Wen","year":"2020","journal-title":"Indones. J. Electr."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"60","DOI":"10.3389\/fnagi.2013.00060","article-title":"Index of alpha\/theta ratio of the electroencephalogram: A new marker for Alzheimer\u2019s disease","volume":"5","author":"Schmidt","year":"2013","journal-title":"Front. Aging Neurosci."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1016\/j.clinph.2021.05.012","article-title":"Resting-state EEG alpha\/theta power ratio discriminates early-onset Alzheimer\u2019s disease from healthy controls","volume":"132","author":"Fide","year":"2021","journal-title":"Clin. Neurophysiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"18706","DOI":"10.1038\/s41598-022-21951-5","article-title":"Implication of EEG theta\/alpha and theta\/beta ratio in Alzheimer\u2019s and Lewy body disease","volume":"12","author":"Baik","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"756","DOI":"10.1016\/j.clinph.2021.01.001","article-title":"Resting-state EEG alpha\/theta ratio related to neuropsychological test performance in Parkinson\u2019s Disease","volume":"132","author":"Bocanegra","year":"2021","journal-title":"Clin. Neurophysiol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Zawi\u015blak-Fornagiel, K., Ledwo\u0144, D., Bugdol, M., Romaniszyn-Kania, P., Ma\u0142ecki, A., Gorzkowska, A., and Mitas, A.W. (2023). The increase of theta power and decrease of alpha\/theta ratio as a manifestation of cognitive impairment in parkinson\u2019s disease. J. Clin. Med., 12.","DOI":"10.3390\/jcm12041569"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Miltiadous, A., Tzimourta, K.D., Afrantou, T., Ioannidis, P., Grigoriadis, N., Tsalikakis, D.G., Angelidis, P., Tsipouras, M.G., Glavas, E., and Giannakeas, N. (2023). A Dataset of Scalp EEG Recordings of Alzheimer\u2019s Disease, Frontotemporal Dementia and Healthy Subjects from Routine EEG. Data, 8.","DOI":"10.3390\/data8060095"},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Miltiadous, A., Tzimourta, K.D., Giannakeas, N., Tsipouras, M.G., Afrantou, T., Ioannidis, P., and Tzallas, A.T. (2021). Alzheimer\u2019s disease and frontotemporal dementia: A robust classification method of EEG signals and a comparison of validation methods. Diagnostics, 11.","DOI":"10.3390\/diagnostics11081437"},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Miltiadous, A., Tzimourta, K.D., Afrantou, T., Ioannidis, P., Grigoriadis, N., Tsalikakis, D.G., Angelidis, P., Tsipouras, M.G., Glavas, E., and Giannakeas, N. (2023). A Dataset of EEG Recordings from: Alzheimer\u2019s Disease, Frontotemporal Dementia and Healthy Subjects. OpenNeuro, Available online: https:\/\/openneuro.org\/datasets\/ds004504\/versions\/1.0.2\/file-display\/README.","DOI":"10.3390\/data8060095"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.jneumeth.2003.10.009","article-title":"EEGLAB: An open source toolbox for analysis of single-trial EEG dynamics including independent component analysis","volume":"134","author":"Delorme","year":"2004","journal-title":"J. Neurosci. Methods"},{"key":"ref_33","unstructured":"Miyakoshi, M., and Kothe, C. (2023, December 05). Clean_Rawdata. Version 2.1. Available online: https:\/\/github.com\/sccn\/clean_rawdata\/wiki."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"601","DOI":"10.3389\/fnins.2017.00601","article-title":"MATLAB Toolboxes for Reference Electrode Standardization Technique (REST) of Scalp EEG","volume":"11","author":"Dong","year":"2017","journal-title":"Front. Neurosci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1007\/s10548-019-00707-x","article-title":"Which Reference Should We Use for EEG and ERP practice?","volume":"32","author":"Yao","year":"2019","journal-title":"Brain Topogr."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"837","DOI":"10.2307\/2531595","article-title":"Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach","volume":"44","author":"DeLong","year":"1988","journal-title":"Biometrics"},{"key":"ref_37","first-page":"451","article-title":"Area under the Precision-Recall Curve: Point Estimates and Confidence Intervals","volume":"8190","author":"Boyd","year":"2013","journal-title":"Adv. Inf. Syst. Eng."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Davis, J., and Goadrich, M. (2006, January 25\u201329). The relationship between Precision-Recall and ROC curves. Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, USA.","DOI":"10.1145\/1143844.1143874"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1002\/1097-0142(1950)3:1<32::AID-CNCR2820030106>3.0.CO;2-3","article-title":"Index for rating diagnostic tests","volume":"3","author":"Youden","year":"1950","journal-title":"Cancer"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"307","DOI":"10.3389\/fpubh.2017.00307","article-title":"Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice","volume":"5","author":"Trevethan","year":"2017","journal-title":"Front. Public Health"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"505","DOI":"10.1002\/jmri.22466","article-title":"Standardizing predictive values in diagnostic imaging research","volume":"33","author":"Heston","year":"2011","journal-title":"J. Magn. Reson. Imaging"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1097\/POC.0b013e318246a5d6","article-title":"Diagnostic accuracy-part 1: Basic concepts: Sensitivity and specificity, ROC analysis, STARD statement","volume":"11","author":"Simundic","year":"2012","journal-title":"Point Care"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2673","DOI":"10.1161\/STROKEAHA.115.009598","article-title":"Stroke and Neurodegeneration Induce Different Connectivity Aberrations in the Insula","volume":"46","author":"Fraiman","year":"2015","journal-title":"Stroke"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1001\/archneurol.2007.38","article-title":"Frontal paralimbic network atrophy in very mild behavioral variant frontotemporal dementia","volume":"65","author":"Seeley","year":"2008","journal-title":"Arch. Neurol."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3022","DOI":"10.1093\/brain\/aww231","article-title":"Your perspective and my benefit: Multiple lesion models of self-other integration strategies during social bargaining","volume":"139","author":"Melloni","year":"2016","journal-title":"Brain"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1212\/WNL.0b013e31829a33f8","article-title":"Brain network connectivity assessed using graph theory in frontotemporal dementia","volume":"81","author":"Agosta","year":"2013","journal-title":"Neurology"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/S0926-6410(00)00086-0","article-title":"Frontal midline theta rhythm is correlated with cardiac autonomic activities during the performance of an attention demanding meditation procedure","volume":"11","author":"Kubota","year":"2001","journal-title":"Brain Res. Cogn. Brain Res."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1016\/j.nrl.2013.02.010","article-title":"Bradycardia in frontotemporal dementia","volume":"29","year":"2014","journal-title":"Neurolog\u00eda"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"637","DOI":"10.1016\/j.neuroimage.2004.01.047","article-title":"The thalamus as the generator and modulator of EEG alpha rhythm: A combined PET\/EEG study with lorazepam challenge in humans","volume":"22","author":"Schreckenberger","year":"2004","journal-title":"NeuroImage"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"812222","DOI":"10.3389\/fnins.2022.812222","article-title":"Frontotemporal dementia and glucose metabolism","volume":"16","author":"Garrett","year":"2022","journal-title":"Front. Neurosci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2487","DOI":"10.1097\/00001756-200212200-00022","article-title":"Simultaneous EEG and fMRI of the alpha rhythm","volume":"13","author":"Goldman","year":"2002","journal-title":"Neuroreport"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"357","DOI":"10.1177\/1073858405277450","article-title":"Thalamic mechanisms of EEG alpha rhythms and their pathological implications","volume":"11","author":"Hughes","year":"2005","journal-title":"Neuroscientist"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"675","DOI":"10.1016\/j.nicl.2018.02.019","article-title":"Thalamic atrophy in frontotemporal dementia\u2014Not just a C9orf72 problem","volume":"18","author":"Bocchetta","year":"2018","journal-title":"NeuroImage Clin."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1560","DOI":"10.1126\/science.1055465","article-title":"Modulation of oscillatory neuronal synchronization by selective visual attention","volume":"291","author":"Fries","year":"2001","journal-title":"Science"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1016\/S0006-3223(99)00306-6","article-title":"Hippocampus and entorhinal cortex in frontotemporal dementia and Alzheimer\u2019s disease: A morphometric MRI study","volume":"47","author":"Laakso","year":"2000","journal-title":"Biol. Psychiatry"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"11037","DOI":"10.1073\/pnas.88.24.11037","article-title":"Magnetic field tomography of coherent thalamocortical 40-Hz oscillations in humans","volume":"88","author":"Ribary","year":"1991","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.3758\/s13415-018-0622-4","article-title":"Enhancing theory of mind in behavioural variant frontotemporal dementia with transcranial direct current stimulation","volume":"18","author":"Cotelli","year":"2018","journal-title":"Cogn. Affect. Behav. Neurosci."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"43","DOI":"10.3389\/fnhum.2018.00043","article-title":"EEG Beta Oscillations in the Temporoparietal Area Related to the Accuracy in Estimating Others\u2019 Preference","volume":"12","author":"Park","year":"2018","journal-title":"Front. Hum. Neurosci."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"2715","DOI":"10.2147\/NDT.S170989","article-title":"Neuronal connectivity in major depressive disorder: A systematic review","volume":"14","author":"Helm","year":"2018","journal-title":"Neuropsychiat. Dis. Treat."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"429","DOI":"10.1016\/j.cortex.2010.12.002","article-title":"Working memory, attention, and executive function in Alzheimer\u2019s disease and frontotemporal dementia","volume":"48","author":"Stopford","year":"2012","journal-title":"Cortex"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"fcac344","DOI":"10.1093\/braincomms\/fcac344","article-title":"Mapping behavioural, cognitive and affective transdiagnostic dimensions in frontotemporal dementia","volume":"5","author":"Ramanan","year":"2023","journal-title":"Brain Commun."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1093\/brain\/awaa097","article-title":"Redefining the multidimensional clinical phenotypes of frontotemporal lobar degeneration syndromes","volume":"143","author":"Murley","year":"2020","journal-title":"Brain J. Neurol."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"534","DOI":"10.1037\/a0018167","article-title":"Dementia: Continuum or distinct entity?","volume":"25","author":"Walters","year":"2010","journal-title":"Psychol. Aging"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1016\/j.cnp.2017.07.002","article-title":"A revised glossary of terms most commonly used by clinical electroencephalographers and updated proposal for the report format of the EEG findings. Revision 2017","volume":"2","author":"Kane","year":"2017","journal-title":"Clin. Neurophysiol. Pract."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"8406","DOI":"10.1111\/ejn.14992","article-title":"Identifying key factors for improving ICA-based decomposition of EEG data in mobile and stationary experiments","volume":"54","author":"Klug","year":"2021","journal-title":"Eur. J. Neurosci."}],"container-title":["Medicina"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1648-9144\/59\/12\/2155\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T21:37:46Z","timestamp":1760132266000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1648-9144\/59\/12\/2155"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,13]]},"references-count":65,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2023,12]]}},"alternative-id":["medicina59122155"],"URL":"https:\/\/doi.org\/10.3390\/medicina59122155","relation":{},"ISSN":["1648-9144"],"issn-type":[{"value":"1648-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,12,13]]}}}